Time-Based Learning Curve for Robotic-Assisted Total Knee Arthroplasty: A Multicenter Study

Abstract

Robotic-assisted total knee arthroplasty (RA-TKA) has been shown to improve the accuracy of bone resection, reduce radiographic outliers, and decrease iatrogenic injury. However, it has also been shown that RA-TKA surgical times can be longer than manual surgery during adoption. The purpose of this article was to investigate (1) the characteristics of the operative time curves and trends, noting the amount of surgeons who improved, for those who performed at least 12 cases (based on initial modeling); (2) the proportion of RA surgeons who achieved the same operative times for RA-TKA as compared with manual TKAs; and (3) the number of RA-TKA cases until a steady-state operative time was achieved. TKA operative times were collected from 30 hospitals for 146 surgeons between January 1, 2016, and December 31, 2019. A hierarchical Bayesian model was used to estimate the difference between the mean RA-TKA times by case interval and the weighted baseline for manual times. The learning curve was observed at the 12th case. Therefore, operative times were analyzed for each surgeon who performed at least 12 RA-TKA cases to determine the percentage of these surgeons who trended toward a decrease or increase in their times. These surgeons were further analyzed to determine the proportion who achieved the same operating times as manual TKAs. A further hierarchical Bayesian model was used to determine when these surgeons achieved steady-state operative times. There were 60 surgeons (82%) who had decreasing surgical times over the first 12 RA-TKA cases. The remaining 13 (18%) had increasing surgical times (mean increase of 0.59 minutes/case). Approximately two-thirds of the surgeons (64%) achieved the same operating times as manual cases. The steady-state time neutrality occurred between 15 and 20 cases and beyond. This study demonstrated the learning curve for a large cohort of RA-TKAs. This model demonstrated a learning curve between 15 and 20 cases and beyond. These are important findings for this innovative technology.

Keywords

total knee arthroplasty - robotic-assisted - learning curve - multicenter - Bayesian model

Publikationsverlauf

Eingereicht: 17. März 2021

Angenommen: 25. Januar 2022

Artikel online veröffentlicht:
07. März 2022

• References

• 1 Batailler C, Fernandez A, Swan J. et al. MAKO CT-based robotic arm-assisted system is a reliable procedure for total knee arthroplasty: a systematic review. Knee Surg Sport Traumatol Arthrosc 2021; 29 (11) 3585-3598
• 2 Bargren JH, Blaha JD, Freeman MAR. Alignment in total knee arthroplasty. Correlated biomechanical and clinical observations. Clin Orthop Relat Res 1983; (173) 178-183
• 3 Bonner TJ, Eardley WGP, Patterson P, Gregg PJ. The effect of post-operative mechanical axis alignment on the survival of primary total knee replacements after a follow-up of 15 years. J Bone Joint Surg Ser B 2011; 93 (09) 1217-1222
• 4 Moreland JR. Mechanisms of failure in total knee arthroplasty. Clin Orthop Relat Res 1988; (226) 49-64
• 5 Oswald MH, Jakob RP, Schneider E, Hoogewoud HM. Radiological analysis of normal axial alignment of femur and tibia in view of total knee arthroplasty. J Arthroplasty 1993; 8 (04) 419-426
• 6 Ranawat CS, Boachie-Adjei O. Survivorship analysis and results of total condylar knee arthroplasty. Eight- to 11-year follow-up period. Clin Orthop Relat Res 1988; (226) 6-13
• 7 Vaidya NV, Deshpande AN, Panjwani T, Patil R, Jaysingani T, Patil P. Robotic-assisted TKA leads to a better prosthesis alignment and a better joint line restoration as compared to conventional TKA: a prospective randomized controlled trial. Knee Surg Sport Traumatol Arthrosc 2022; 30 (02) 621-626
• 8 King CA, Jordan M, Bradley AT, Wlodarski C, Tauchen A, Puri L. Transitioning a practice to robotic total knee arthroplasty is correlated with favorable short-term clinical outcomes—a single surgeon experience. J Knee Surg 2022; 35 (01) 78-82
• 9 Kayani B, Konan S, Huq SS, Tahmassebi J, Haddad FS. Robotic-arm assisted total knee arthroplasty has a learning curve of seven cases for integration into the surgical workflow but no learning curve effect for accuracy of implant positioning. Knee Surg Sport Traumatol Arthrosc 2019; 27 (04) 1132-1141
• 10 Kayani B, Konan S, Pietrzak JRT, Huq SS, Tahmassebi J, Haddad FS. The learning curve associated with robotic-arm assisted unicompartmental knee arthroplasty: a prospective cohort study. Bone Joint J 2018; 100-B [phone]
• 11 Sodhi N, Khlopas A, Piuzzi NS. et al. The learning curve associated with robotic total knee arthroplasty. J Knee Surg 2018; 31 (01) 17-21
• 12 Kruschke JK. Bayesian estimation supersedes the t test. J Exp Psychol Gen 2013; 142 (02) 573-603
• 13 Kruschke JK, Aguinis H, Joo H. The time has come: bayesian methods for data analysis in the organizational sciences. Organ Res Methods 2012; 15 (04) 722-752
• 14 Kruschke JK, Liddell TM. The Bayesian new statistics: hypothesis testing, estimation, meta-analysis, and power analysis from a Bayesian perspective. Psychon Bull Rev 2018; 25 (01) 178-206
• 15 Gelman A, Tuerlinckx F. Type S error rates classical and Bayesian single and multiple compparison procedures. Comput Stat 2000; 15: 373-390
• 16 Singh V, Fiedler B, Simcox T, Aggarwal VK, Schwarzkopf R, Meftah M. Does the use of intraoperative technology yield superior patient outcomes following total knee arthroplasty?. J Arthroplasty 2021; 36 (7S): S227-S232
• 17 Vermue H, Luyckx T, Winnock de Grave P. et al. Robot-assisted total knee arthroplasty is associated with a learning curve for surgical time but not for component alignment, limb alignment and gap balancing. Knee Surg Sport Traumatol Arthrosc 2022; 30 (02) 593-602
• 18 Grau L, Lingamfelter M, Ponzio D. et al. Robotic arm assisted total knee arthroplasty workflow optimization, operative times and learning curve. Arthroplast Today 2019; 5 (04) 465-470
• 19 Marchand KB, Ehiorobo J, Mathew KK, Marchand RC, Mont MA. Learning curve of robotic-assisted total knee arthroplasty for a high-volume surgeon. J Knee Surg 2022; 35 (04) 409-415
• 20 Scholl LY, Hampp EL, De Souza KM. et al. How does robotic-arm assisted technology influence total knee arthroplasty implant placement for surgeons in fellowship training?. J Knee Surg 2022; 35 (02) 198-203